Breast cancer is the most frequently diagnosed cancer in the US with an estimated 211,240 new cases of invasive breast cancer and 58,490 new cases of in situ breast cancer in 2005. The mortality rate of 2.3% per year translates into more than 40,000 deaths of the 2.3 million American women with breast cancer (American Cancer Society, 2005). Mortality results primarily from complications of metastatic breast cancer, which has a poor clinical outcome in spite of transient improvement seen with newer pharmaceuticals that target specific cancer-associated proteins, such as the antibody trastuzumab (Herceptin). Therefore, there is a significant need for new drugs for the treatment of breast cancer. TNF-converting enzyme (TACE or ADAM17) is a promising anti-cancer target. TACE plays a critical role in the maturation and release of many proteins including the epidermal growth factor receptor (EGFR) ligands, TGFa, amphiregulin, heparin binding EGF, betacellulin, and epiregulin. Because increased EGFR activity is associated with breast cancer, and antibodies that block specific EGFR receptors have demonstrated some clinical efficacy, it is expected that TACE inhibitors will prove potent anti-cancer agents, because they will simultaneously inhibit several types of EGFRs by limiting production of their cognate ligands. Therefore, we propose to select antibody (Fab) inhibitors of TACE enzymatic activity from a phagemid library using a novel E. coli survival-based selection. We will then optimize their pharmacological properties by selection for mutants that confer increased E. coli survival and higher affinity binding. We will test the most specific, high affinity Fabs to determine how well they inhibit breast cancer cell proliferation in culture. Fabs that display significant inhibition of breast cancer growth hold great potential as new therapeutic agents against breast cancer, and will be further characterized for anti-tumor activity in vivo in phase II studies.This project seeks to discover a new antibody-based drug to treat metastatic breast cancer. [unreadable] [unreadable] [unreadable]